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@ARTICLE{MllerLinow:188553,
      author       = {Müller-Linow, Mark and Pinto-Espinosa, Francisco and
                      Scharr, Hanno and Rascher, Uwe},
      title        = {{T}he leaf angle distribution of natural plant populations:
                      assessing the canopy with a novel software tool},
      journal      = {Plant methods},
      volume       = {11},
      number       = {1},
      issn         = {1746-4811},
      address      = {London},
      publisher    = {BioMed Central},
      reportid     = {FZJ-2015-01908},
      pages        = {11},
      year         = {2015},
      abstract     = {Background Three-dimensional canopies form complex
                      architectures with temporally and spatially changing leaf
                      orientations. Variations in canopy structure are linked to
                      canopy function and they occur within the scope of genetic
                      variability as well as a reaction to environmental factors
                      like light, water and nutrient supply, and stress. An
                      important key measure to characterize these structural
                      properties is the leaf angle distribution, which in turn
                      requires knowledge on the 3-dimensional single leaf surface.
                      Despite a large number of 3-d sensors and methods only a few
                      systems are applicable for fast and routine measurements in
                      plants and natural canopies. A suitable approach is stereo
                      imaging, which combines depth and color information that
                      allows for easy segmentation of green leaf material and the
                      extraction of plant traits, such as leaf angle distribution.
                      Results We developed a software package, which provides
                      tools for the quantification of leaf surface properties
                      within natural canopies via 3-d reconstruction from stereo
                      images. Our approach includes a semi-automatic selection
                      process of single leaves and different modes of surface
                      characterization via polygon smoothing or surface model
                      fitting. Based on the resulting surface meshes leaf angle
                      statistics are computed on the whole-leaf level or from
                      local derivations. We include a case study to demonstrate
                      the functionality of our software. 48 images of small sugar
                      beet populations (4 varieties) have been analyzed on the
                      base of their leaf angle distribution in order to
                      investigate seasonal, genotypic and fertilization effects on
                      leaf angle distributions. We could show that leaf angle
                      distributions change during the course of the season with
                      all varieties having a comparable development. Additionally,
                      different varieties had different leaf angle orientation
                      that could be separated in principle component analysis. In
                      contrast nitrogen treatment had no effect on leaf angles.
                      Conclusions We show that a stereo imaging setup together
                      with the appropriate image processing tools is capable of
                      retrieving the geometric leaf surface properties of plants
                      and canopies. Our software package provides whole-leaf
                      statistics but also a local estimation of leaf angles, which
                      may have great potential to better understand and quantify
                      structural canopy traits for guided breeding and optimized
                      crop management.},
      cin          = {IBG-2},
      ddc          = {580},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {582 - Plant Science (POF3-582) / DPPN - Deutsches Pflanzen
                      Phänotypisierungsnetzwerk (BMBF-031A053A)},
      pid          = {G:(DE-HGF)POF3-582 / G:(DE-Juel1)BMBF-031A053A},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000350857300001},
      pubmed       = {pmid:25774205},
      doi          = {10.1186/s13007-015-0052-z},
      url          = {https://juser.fz-juelich.de/record/188553},
}